Neural networks octanol-water partition

Molnar, L, Keserii, G. M., Papp A., Gulyas, Z., Darvas, F. A neural network based prediction of octanol-water partition coefficients using atomicS fragmental descriptors. Bioorg. Med. Chtm. Lett. 2004, 14, 851-853. 

Breindl, A., Beck, B., Qark, T., Glen, R. C. Prediction of the n-octanol/water partition coefficient, log P, using a combination of semiempirical MO-calculations and a neural network. J. Mol. Model. 1997, 3, 142-155. 

Tetko, I. V., Tandiuk, V. Y., Villa, A. E. Prediction of n-octanol/water partition coeffidents from PHYSPROP database using artifidal neural networks and E-state indices./. Chem. Inf. Comput. Sci. 2001,... 

Associative neural networks (ASNN) Aqueous solubility, octanol-water partition (logP, logD) Quantitative Error No [13-15]... 

Zheng, G., Huang, W.H., Lu, X.H. (2003) Prediction of n-octanol/water partition coefficients for polychlorinated dibenzo-p-dioxins using a general regression neural network. AnalBioanal. Chem. 376, 680-685. 

Tetko IV, Tanchuk VY, Villa AE. Prediction of H-octanol/water partition coefficients from PHYSPROP database using artificial neural networks and E-state indices. J Chem Inf Comput Sci 2001 41 1407-21. 

Yaffe, D., Cohen, Y, Espinosa, G Arenas, A. and Giralt, E. (2002) Euzzy ARTMAP and back-propagation neural networks based quantitative structure-property relationships (QSPRs) for octanol-water partition coefficient of organic compounds. /. Chem. Inf. Comput. Sci., 42, 162-183. 

Calleja et al. studied the relationships between acute toxicity toward five aquatic non-vertebrates and humans, and molecular structure for 38 structurally diverse chemicals (60). These chemicals were from the 50 priority chemicals prescribed by the Multicenter Evaluation of In Vitro Cytotoxicity (MEIC) program. Nonlinear models, derived from PLS regression or BP neural networks, appear to be better than linear models for describing the relation between acute toxicity and molecular structure. BP neural net models, in turn, outperformed nonlinear models obtained from PLS regression. They determined that the physicochemical properties most important for human acute toxicity were the -octanol-water partition coefficient and heat of formation. 

D 3D AD ADME ADMET ANN ARD BCI BCUT BNN C4.5 CART ClogP CoMFA CV Two dimensional Three dimensional Applicability domain Absorption, distribution metabolism, and excretion Absorption, distribution metabolism, excretion, and toxicity Artificial neural network Automatic relevance determination Bernard chemical information Burden, CAS, University of Texas descriptors Bayesian neural network Decision trees using information entropy Classification and regression tree Calculated partition coefficient between octanol and water Comparative molecular field analysis Cross-validation... 

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